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Purpose: To introduce a novel deep model‐based architecture (DMBA), SPICER, that uses pairs of noisy and undersampled k‐space measurements of the same object to jointly train a model for MRI reconstruction and automatic coil sensitivity estimation. Methods: SPICER consists of two modules to simultaneously reconstructs accurate MR images and estimates high‐quality coil sensitivity maps (CSMs). The first module, CSM estimation module, uses a convolutional neural network (CNN) to estimate CSMs from the raw measurements. The second module, DMBA‐based MRI reconstruction module, forms reconstructed images from the input measurements and the estimated CSMs using both the physical measurement model and learned CNN prior. With the benefit of our self‐supervised learning strategy, SPICER can be efficiently trained without any fully sampled reference data. Results: We validate SPICER on both open‐access datasets and experimentally collected data, showing that it can achieve state‐of‐the‐art performance in highly accelerated data acquisition settings (up to 10×$$ 10\times $$). Our results also highlight the importance of different modules of SPICER—including the DMBA, the CSM estimation, and the SPICER training loss—on the final performance of the method. Moreover, SPICER can estimate better CSMs than pre‐estimation methods especially when the ACS data is limited. Conclusion: Despite being trained on noisy undersampled data, SPICER can reconstruct high‐quality images and CSMs in highly undersampled settings, which outperforms other self‐supervised learning methods and matches the performance of the well‐known E2E‐VarNet trained on fully sampled ground‐truth data. [ABSTRACT FROM AUTHOR]

The uncertainty and unknowability of emerging infectious diseases have caused many major public health and security incidents in recent years. As a new tick‐borne disease, Dabieshan tick virus (DBTV) necessitate systematic epidemiological and spatial distribution analysis. In this study, tick samples from Liaoning Province were collected and used to evaluate distribution of DBTV in ticks. Outbreak points of DBTV and the records of the vector Haemaphysalis longicornis in China were collected and used to establish a prediction model using niche model combined with environmental factors. We found that H. longicornis and DBTV were widely distributed in Liaoning Province. The risk analysis results showed that the DBTV in the eastern provinces of China has a high risk, and the risk is greatly influenced by elevation, land cover, and meteorological factors. The risk geographical area predicted by the model is significantly larger than the detected positive areas, indicating that the etiological survey is seriously insufficient. This study provided molecular and important epidemiological evidence for etiological ecology of DBTV. The predicted high‐risk areas indicated the insufficient monitoring and risk evaluation and the necessity of future monitoring and control work. [ABSTRACT FROM AUTHOR]

Engineering borate glass structure by simple compositional modification is essential to meet the particular demands from both industrial and photonic research communities. In this article, we demonstrate how the mixing of Li2O with Na2O, K2O, or Cs2O influences the relative abundance of 3‐ and 4‐coordinated borons in the glass network, as exhibited by nuclear magnetic resonance (NMR) and Raman spectra. A systematic study is given of the alkali mixing effect on the glass properties including: glass transition temperature, microhardness, density, refractive index, and particularly the near‐infrared photoluminescence properties (eg, bandwidth and lifetime) of Er3+ which has been barely studied in mixed alkali borate glasses. It is interesting to note that the glass transition temperature, refractive index and emission lifetime of Er3+ manifest mixed alkali effect, in sharp contrast with microhardness, density, and emission bandwidth which vary monotonically upon the alkali mixing. The possible causes for the differences are discussed in the light of the compositional dependence of boron species and nonbridging oxygen upon alkali mixing. [ABSTRACT FROM AUTHOR]

Abstract: Controllable and repeatable crystal imperfection modulation engineering (CIME) is important for the development of semiconductor science and technology. However, for wide band gap semiconductors (WBGSs), there still lacks universal and reliable CIME. Here, based on the general idea of chemical composition complete expression design, a well‐designed, repeatable, and feasible CIME for ZnO is introduced, making free modulation of carrier in WBGS become possible. Briefly, this extraordinary CIME is dominated by two innovative procedures: an electrochemical doping and a strong oxidizing atmosphere annealing. The proposed CIME is a repeatable and universal carrier modulation project, which holds technological promise for various WBGS‐based semiconductor devices. Benefiting from this CIME, an α particle detector which operating at a high electric field of 107 V cm−1 can be fabricated successfully. [ABSTRACT FROM AUTHOR]

The cover page for the February 2018 issue, Vol. 4 and issue No. 2 of the journal "Advanced Electronic Materials" is presented.